基于优化自导向量子生成对抗网络的云计算资源高效利用调度框架,提高性能和可靠性

IF 2.5 4区 计算机科学 Q3 TELECOMMUNICATIONS
P. M. Sithar Selvam, S. Shabana Begum, Yogesh Pingle, Santhosh Srinivasan
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引用次数: 0

摘要

云计算支持动态资源访问,但由于虚拟机(VM)管理中的干扰和性能限制,有效的资源分配仍然具有挑战性。在云计算中,有效的资源分配对于最小化干扰和优化虚拟机性能至关重要。本文提出了一种基于草原土拨鼠优化算法的自导向量子生成对抗网络(SGQGAN-PDOA)来动态地重新分配虚拟机之间的任务。该框架集成了Inception Transformer (IT)进行特征提取和Spatial Distribution-Principal Component Analysis (SD-PCA)进行特征约简,提高了处理效率。该模型使用CloudSim在Java中实现,提高了资源利用率,在200毫秒的处理时间内实现了150个vm的80%的可靠性。实验结果表明,显著减少了等待时间、响应时间和负载不平衡,优于现有的方法。通过利用量子生成建模和优化,这种方法增强了动态云环境中的可伸缩性、能源效率和系统响应能力。研究结果表明,量子启发的调度框架为云计算中的自适应和高性能资源管理提供了一个有前途的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Optimized Self-Guided Quantum Generative Adversarial Network Based Scheduling Framework for Efficient Resource Utilization in Cloud Computing to Enhance Performance and Reliability

Optimized Self-Guided Quantum Generative Adversarial Network Based Scheduling Framework for Efficient Resource Utilization in Cloud Computing to Enhance Performance and Reliability

Cloud computing enables dynamic resource access, but efficient resource allocation remains challenging due to interference and performance limitations in virtual machine (VM) management. Efficient resource allocation in cloud computing is crucial for minimizing interference and optimizing virtual machine (VM) performance. This study proposes a Self-Guided Quantum Generative Adversarial Network with Prairie Dog Optimization Algorithm (SGQGAN-PDOA) to reallocate tasks across VMs dynamically. The framework integrates Inception Transformer (IT) for feature extraction and Spatial Distribution–Principal Component Analysis (SD-PCA) for feature reduction, enhancing processing efficiency. Implemented in Java with CloudSim, the proposed model improves resource utilization, achieving 80% reliability for 150 VMs with a 200 ms processing time. Experimental results demonstrate significant reductions in waiting time, response time, and load imbalance, outperforming existing methods. By leveraging quantum generative modeling and optimization, this approach enhances scalability, energy efficiency, and system responsiveness in dynamic cloud environments. The findings suggest that quantum-inspired scheduling frameworks offer a promising solution for adaptive and high-performance resource management in cloud computing.

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来源期刊
CiteScore
8.90
自引率
13.90%
发文量
249
期刊介绍: ransactions on Emerging Telecommunications Technologies (ETT), formerly known as European Transactions on Telecommunications (ETT), has the following aims: - to attract cutting-edge publications from leading researchers and research groups around the world - to become a highly cited source of timely research findings in emerging fields of telecommunications - to limit revision and publication cycles to a few months and thus significantly increase attractiveness to publish - to become the leading journal for publishing the latest developments in telecommunications
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